Technical Articles

For years high-speed imaging has provided engineers with detailed analysis of projective tracking, missile launches, combustion testing, engine testing, fuselage testing, component testing, materials testing, flow visualization and more. There are several companies that manufacture high-speed cameras, so how do you decide which company to buy from and which model of camera to buy? This article discusses the many factors that are important to consider when purchasing a high-speed camera for aerospace testing.

Midwave (MWIR) infrared light is important in many hardware applications and optical filters are critical to success. Some simple practices can help avoid over specifying filter characteristics and driving up costs.

Augmented reality must still surpass major technical hurdles, particularly in the way AR devices deliver images to the eye. Already, systems that were once promising have been analyzed and largely discarded.

MWIR cameras capture images below the red end of the visible color spectrum at the peak absorption of emissions of hydrocarbon gases such as methane, propane, and butane, helping guarantee the safety of oil and gas industry workers, as well as protecting the environment and reducing repair costs.

Safe advanced driver assist system (ADAS) vehicles and autonomous vehicles (AV) require the use of sensors to deliver scene data adequate for the detection and classification algorithms to autonomously navigate under all conditions. This requirement cannot be adequately met with just visible cameras, sonar, and radar sensors. Thermal, or longwave infrared (LWIR), cameras can detect and classify pedestrians in darkness, fog, and sun glares, and deliver improved technical and logistical integration for ADAS systems. This white paper is Part 4 of the series how thermal infrared cameras overcome technical and logistical integrations challenges in autonomous driving.

Safe advanced driver assist system (ADAS) vehicles and autonomous vehicles (AV) require the use of sensors to deliver scene data adequate for the detection and classification algorithms to autonomously navigate under all conditions. This requirement cannot be adequately met with just visible cameras, sonar, and radar sensors, as they do not meet many safety concerns in real conditions. Thermal, or longwave infrared (LWIR), cameras can detect and classify pedestrians in darkness, fog, and sun glares, delivering improved situational awareness in ADAS and AV. This white paper is Part 3 of the series on how thermal infrared cameras deliver an affordable, scalable and integrative solution over other sensor technologies for autonomous driving.

Safe advanced driver assist system (ADAS) vehicles and autonomous vehicles (AV) require the use of sensors to deliver scene data adequate for the detection and classification algorithms to autonomously navigate under all conditions. This requirement cannot be adequately met with just visible cameras, sonar, and radar sensors, as they do not meet many safety concerns in real conditions. Thermal, or longwave infrared (LWIR), cameras can detect and classify pedestrians in darkness, fog, and sun glares, delivering improved situational awareness in ADAS and AV. This white paper is Part 2 of the series on the technical advantages that thermal infrared cameras deliver over other technologies for autonomous driving.

Safe advanced driver assist system (ADAS) vehicles and autonomous vehicles (AV) require the use of sensors to deliver scene data adequate for the detection and classification algorithms to autonomously navigate under all conditions for SAE automation level 5. This challenging requirement cannot be adequately met with just visible cameras, sonar, and radar sensors. As a solution, thermal, or longwave infrared (LWIR), cameras can detect and classify pedestrians in darkness, fog, and sun glares, delivering improved situational awareness in ADAS and AV. This white paper is Part 1 of a series on why thermal infrared cameras are a necessity for autonomous driving.

Predicting new trends in technology is not a simple task. The machine vision industry is no exception as new imaging technologies are constantly improving efficiencies, costs, and intelligence. In this white paper, Pleora Technologies offers some thoughts about the future trends in machine vision technologies.